Readit Newssnasan commented on Show HN: An A2A-compatible, open-source framework for multi-agent networks github.com/openagents-org... · Posted by u/snasan
What is the difference from AutoGen?
Frameworks like AutoGen are used to build individual agents or agent teams, while OpenAgents is designed to connect countless such teams and individuals into a vast, dynamic, and scalable ecosystem.
> Star Us on GitHub and Get Exclusive Day 1 Badge for Your Networks
This made me close the tab.
Stars have been gamed for awhile on GitHub, but given the single demo, my best guess is that this is trying to build hype before having any real utility.
If being thorough is wrong, then what exactly is right?
Good to see a2a getting more attention.
If you are a rustacean, We are building something in the a2a space as well. Tho we don't have sudden increase in stars :/
A2A is hard tto ignore, especially for anyone working on multi-agent systems.
That doesn’t necessarily mean it is malware. Is it not possible that they just paid for some kind of PR or fake stars?
Just playing devils advocate as I think your accusation isn’t based on much merit and is quite a big claim to make.
If you've tried it, you know why everyone's so happy to star it.
Nice work — making multi-agent networks A2A-compatible in an open-source framework looks very promising.
Thank you! That really means a lot. Making A2A work seamlessly was a key goal for us. We can't wait to see what kind of networks and collaborations people start building.
Definitely not malware: https://www.star-history.com/#openagents-org/openagents&type...
Hey, I still remember October 9th so well — that was the day we first went public with our project! I was so excited telling all my friends about it on social media. We'd been working towards this for months, getting everything ready.
In the late 90s and early 2000s there was a bunch of academic research into collaborative multi-agent systems. This included things like communication protocols, capability discovery, platforms, and some AI. The classic and over-used example was travel booking -- a hotel booking agent, a flight booking agent, a train booking agent, etc all collaborating to align time, cost, location. The cooperative agents could add themselves and their capabilities to the agent community and the potential of the system as a whole would increase, and there would perhaps be cool emergent behaviours that no one had thought of.
This appears, to me, like an LLM-agent descendent of these earlier multi-agent systems.
I lost track of the research after I left academia -- perhaps someone here can fill in the (considerable) blanks from my overview?
Maybe this article can help you. It mentions the multi-agent research boom back in the 1990s. Later, reinforcement learning was incorporated, and by 2017, industrial-scale applications of multi-agent reinforcement learning were even achieved. Neural networks were eventually integrated too. But when LLMs arrived, they upended the entire paradigm. The article also breaks down the architecture of modern asynchronous multi-agent systems, using Microsoft's Magentic One as a key example.
https://medium.com/@openagents/the-end-of-a-15-year-marl-era...